Ramesh Thangarajan
Software Engineer at Google
California, United States
Summary
🤩
Rockstar🎓
Top SchoolRamesh Thangarajan is a senior software engineer based in California with a decade of experience building high-performance database and distributed systems. He has a strong track record in query engines and optimizers, having worked at Cloudera and now contributing to query processing for Spanner at Google. As an Apache Hive committer, he has improved core Hive vectorization, Decimal64 support, and LLAP memory handling—contributions that reflect a focus on performance and memory-efficient implementations in large-scale analytics engines. His background includes enhancing SQL and SPARQL engines at MarkLogic and hands-on experience across storage, network and query layers, plus earlier work tuning production SQL and ETL pipelines. Holding a Master’s in Computer Science from Arizona State University, he blends deep systems expertise with practical optimizations that reduce resource usage and improve query throughput.
10 years of coding experience
12 years of employment as a software developer
Master’s Degree Computer Science, Master’s Degree Computer Science at Arizona State UniversityB.E CSE, B.E CSE at College of Engineering, Guindy
Stackoverflow
1reputation
0reached
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Github Skills (9)
javas10
vectorization10
sql10
apache-hive10
java10
database9
big-data9
databases9
hadoop8
Programming languages (1)
Github contributions (5)
apache/hive
Sep 2019 - Jan 2023
Apache Hive
Role in this project:
Back-end Developer
Back-end DeveloperContributions:77 reviews, 37 commits, 87 PRs in 3 years 4 months
Contributions summary:The user, Ramesh Kumar Thangarajan, is primarily focused on enhancing the Apache Hive backend. His contributions encompass bug fixes and new feature implementations related to vectorization, including the vectorized limit operator, support for Decimal64 operations, and optimizations for group by operations. Furthermore, the user addressed issues with Decimal64 handling in NVL and CASE statements, and also worked on improved memory management for LLAP record readers. These changes demonstrate a focus on improving performance and functionality of Hive's core components.
flinksqlapachebig-dataspark
ramesh0201/hive
Aug 2019 - Mar 2025
Apache Hive
Contributions:471 pushes, 63 branches in 5 years 7 months
flinkapachebig-datasparkdatabase
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